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Träfflista för sökning "WFRF:(Gray Rob) srt2:(2015-2019)"

Search: WFRF:(Gray Rob) > (2015-2019)

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1.
  • Hudson, Lawrence N, et al. (author)
  • The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project
  • 2017
  • In: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 7:1, s. 145-188
  • Journal article (peer-reviewed)abstract
    • The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.
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4.
  • Wilkinson, Mark D., et al. (author)
  • Comment : The FAIR Guiding Principles for scientific data management and stewardship
  • 2016
  • In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 3
  • Journal article (peer-reviewed)abstract
    • There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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  • 2017
  • swepub:Mat__t
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  • Thomas, HS, et al. (author)
  • 2019
  • swepub:Mat__t
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7.
  • 2019
  • Journal article (peer-reviewed)
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  • Result 1-7 of 7

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